GPT-5.5 Pro vs Claude Fable 5.1 | API Pricing and Cost Comparison

Claude Fable 5.1 cuts token costs by $460 on a standard monthly workload

Running 10M input tokens and 2M output tokens through OpenAI bills $660.00, while Anthropic charges $200.00 for the exact same volume. In this gpt-5.5 pro vs claude fable 5.1 pricing breakdown, the unit rate disparity shows a massive gap in operational expenditure for production engineering teams.

Evaluating API tiers requires moving past nominal capabilities to examine baseline rate cards and sustained billing impacts. When analyzing gpt-5.5 pro pricing alongside claude fable 5.1 pricing, engineering leads face an immediate financial divide. OpenAI sets its flagship model rates at premium thresholds, whereas Anthropic offers a significantly lower cost structure across both input and output channels.

For organizations evaluating an api cost comparison between OpenAI vs Anthropic, pricing determines infrastructure scalability. Choosing the wrong model architecture for high throughput operations can inflate monthly cloud invoices by thousands of dollars without delivering a proportional increase in application utility.

How do input and output rate cards compare side by side?

Anthropic charges $10.00 per 1M input tokens and $50.00 per 1M output tokens for Claude Fable 5.1, while OpenAI charges $30.00 per 1M input tokens and $180.00 per 1M output tokens for GPT-5.5 Pro. This establishes a 3x price multiplier on input tokens and a 3.6x multiplier on output tokens in favor of Anthropic.

The stark contrast in output pricing is particularly significant for text generation tasks. Output tokens are consistently the most expensive component of LLM deployments. Paying $180.00 per 1M output tokens on GPT-5.5 Pro versus $50.00 per 1M output tokens on Claude Fable 5.1 means long form generations, code synthesis, or detailed analytical reports cost $130.00 more per million generated tokens on OpenAI infrastructure.

Prompt caching adds another layer to this pricing divide. Claude Fable 5.1 publishes a cached input rate of $0.25 per 1M tokens, reducing input costs by 97.5 percent when reusing prompt contexts. GPT-5.5 Pro publishes no cached input rate, forcing buyers to evaluate all input volume at the full $30.00 per 1M token rack rate regardless of context repetition.

• GPT-5.5 Pro Input Rate: $30.00 per 1M tokens
• GPT-5.5 Pro Output Rate: $180.00 per 1M tokens
• GPT-5.5 Pro Cached Input Rate: None published
• Claude Fable 5.1 Input Rate: $10.00 per 1M tokens
• Claude Fable 5.1 Output Rate: $50.00 per 1M tokens
• Claude Fable 5.1 Cached Input Rate: $0.25 per 1M tokens

What does a 10M input and 2M output workload cost on each model?

On a workload of 10M input and 2M output tokens a month, GPT-5.5 Pro bills $660.00 and Claude Fable 5.1 bills $200.00. This math demonstrates that Claude Fable 5.1 is 230 percent cheaper than GPT-5.5 Pro on that specific monthly volume.

Breaking down the arithmetic highlights where the billing accumulates for engineering teams. For GPT-5.5 Pro, 10M input tokens at $30.00 per 1M equal $300.00, and 2M output tokens at $180.00 per 1M equal $360.00, combining for a monthly total of $660.00. For Claude Fable 5.1, 10M input tokens at $10.00 per 1M equal $100.00, and 2M output tokens at $50.00 per 1M equal $100.00, combining for a monthly total of $200.00. The total delta of $460.00 per month represents a substantial recurring expense difference.

To put these rates into broader perspective within our pricing database, budget flash models charge fractions of these flagship prices. Ling 3.0 Flash by inclusionAI charges $0.021 input and $0.063 output per 1M tokens. Similarly, DeepSeek V4 Flash 0731 by DeepSeek charges $0.04 input and $0.08 output per 1M tokens. While flash models target lightweight utility, the comparison illustrates the premium pricing demanded by frontier reasoning models like GPT-5.5 Pro and Claude Fable 5.1.

How do context windows and output limits compare between models?

GPT-5.5 Pro offers a context window of 1050k tokens, while Claude Fable 5.1 provides a context window of 1000k tokens. Both models feature identical maximum output limits of 128k tokens per request.

The 50k token difference in context window capacity gives GPT-5.5 Pro a slight technical advantage when processing extremely large document repositories or long conversations. However, a 1000k token context window on Claude Fable 5.1 remains sufficient for almost all large context enterprise workloads, including full codebases, legal transcripts, and extensive research archives.

On output generation capacity, neither provider holds an advantage. The shared 128k token maximum output ceiling allows both models to generate long documents, complex code files, and extensive structured data objects in a single API call. The cost to generate that maximum output, however, differs dramatically: a full 128k output generation costs $23.04 on GPT-5.5 Pro ($180.00 / 1M * 0.128M) compared to $6.40 on Claude Fable 5.1 ($50.00 / 1M * 0.128M).

Where does GPT-5.5 Pro win over Claude Fable 5.1?

GPT-5.5 Pro wins on reasoning capabilities, open weights access, and a marginally larger context window of 1050k tokens. Organizations requiring deep logical synthesis or open weights deployment models will find features on OpenAI that Anthropic does not match.

According to capabilities on record, GPT-5.5 Pro covers Reasoning, Long context, and Open weights. For development teams building complex multi-step logical pipelines, the specialized reasoning profile of GPT-5.5 Pro provides targeted functionality. Furthermore, the inclusion of Open weights offers architectural flexibility for enterprise deployments that demand self-hosted or customizable model instances.

In a direct gpt-5.5 pro vs claude fable 5.1 evaluation, the extra 50k tokens of context window capacity (1050k versus 1000k) provides additional headroom for edge cases where prompt size exceeds one million tokens. For teams where open weights and specialized reasoning are mandatory requirements, the higher unit rates of GPT-5.5 Pro may be justified by these distinct capability inclusions.

• Reasoning capabilities on record
• Open weights availability for custom infrastructure
• Slightly larger 1050k token context window

Where does Claude Fable 5.1 win over GPT-5.5 Pro?

Claude Fable 5.1 wins on unit token economics, published prompt caching rates, and capabilities focused on coding and autonomous agents. Anthropic delivers superior financial efficiency for high volume API integrations without sacrificing long context support.

The baseline pricing of $10.00 input and $50.00 output per 1M tokens makes Claude Fable 5.1 substantially more affordable for production pipelines. When factoring in the published prompt caching rate of $0.25 per 1M tokens, high frequency workflows that reuse static prompt headers or system instructions realize exponential cost savings. GPT-5.5 Pro publishes no cached input rate, leaving high volume buyers exposed to full input pricing on every request.

Capabilities on record for Claude Fable 5.1 cover Coding, Long context, and Agents. This capability profile aligns directly with software engineering automation, code generation, and recursive agentic loops where frequent API calls quickly accumulate token costs. In an OpenAI vs Anthropic cost analysis, Claude Fable 5.1 delivers clear economic leadership for software development and agent deployment.

• 230 percent lower billing on standard monthly volumes
• Published $0.25 per 1M tokens cached input rate
• Coding and Agent capabilities on record

Which model wins for high volume chat, long context, and agentic chains?

Claude Fable 5.1 wins for high volume chat and agentic chains, while GPT-5.5 Pro wins specifically when open weights or maximum reasoning performance are required. The 230 percent cost savings of Claude Fable 5.1 make it the recommended default choice for the majority of production deployments.

For high volume chat applications, Claude Fable 5.1 takes the top spot. The combination of $10.00 input, $50.00 output, and $0.25 cached input rates allows conversational platforms to scale economically without facing the $30.00 input and $180.00 output rate card of GPT-5.5 Pro.

For long context work, both models perform exceptionally well with context windows around one million tokens (1050k for GPT-5.5 Pro versus 1000k for Claude Fable 5.1). However, Claude Fable 5.1 wins on cost efficiency for long context workflows due to its lower input rate and prompt caching support. GPT-5.5 Pro is only preferred for long context work if the prompt strictly requires between 1000k and 1050k tokens.

For agentic chains, Claude Fable 5.1 is the decisive winner. Autonomous agents make frequent, iterative API calls that consume heavy prompt tokens and generate continuous outputs. Claude Fable 5.1 is specifically built with Agent and Coding capabilities on record, and its lower pricing prevents agent loop budgets from ballooning. In contrast, running high iteration agent loops on GPT-5.5 Pro at $180.00 per 1M output tokens quickly becomes financially prohibitive. Overall, unless your stack depends on Open weights or specific Reasoning constraints, Claude Fable 5.1 is the clear operational winner in this gpt-5.5 pro vs claude fable 5.1 comparison.

• High Volume Chat Winner: Claude Fable 5.1 ($10.00 input / $50.00 output)
• Long Context Winner: Claude Fable 5.1 (1000k window with $0.25 cached input)
• Agentic Chains Winner: Claude Fable 5.1 (Agent capability + low output rates)
• Open Weights & Reasoning Winner: GPT-5.5 Pro (Open weights + Reasoning capability)